{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cb6e0ab4",
   "metadata": {},
   "source": [
    "# 基于第三方模型自动集成进行时序建模"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "832db3e2",
   "metadata": {},
   "source": [
    "PaddleTS集成了 [scikit-learn][scikit-learn Link] 和 [pyod][pyod Link] 第三方库。在该文档中，我们将介绍如何使用PaddleTS的[第三方模型自动集成][paddlets Link]能力构建时序模型。\n",
    "\n",
    "主要内容包括：  \n",
    "1. 基于第三方模型进行时序预测\n",
    "2. 基于第三方模型进行时序异常检测\n",
    "\n",
    "[scikit-learn Link]: https://scikit-learn.org/stable/index.html\n",
    "[pyod Link]: https://pyod.readthedocs.io/en/latest/index.html\n",
    "[paddlets Link]: https://github.com/PaddlePaddle/PaddleTS/blob/main/paddlets/models/ml_model_wrapper.py#L881"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f780180",
   "metadata": {},
   "source": [
    "# 1. 基于第三方模型进行时序预测\n",
    "\n",
    "第一部分会基于 [scikit-learn][scikit-learn Link] 第三方模型构建时序预测模型。步骤包括：\n",
    "\n",
    "- 1.1 数据导入\n",
    "- 1.2.数据查看\n",
    "- 1.3 数据预处理\n",
    "- 1.4 模型构建\n",
    "- 1.5 模型训练\n",
    "- 1.6 模型预测与评估\n",
    "- 1.7 模型保存  \n",
    "- 1.8 模型加载及推理\n",
    "- 1.9 （可选）自定义样本数据构建函数\n",
    "\n",
    "[scikit-learn Link]: https://scikit-learn.org/stable/index.html"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e89708b",
   "metadata": {},
   "source": [
    "## 1.1 数据导入\n",
    "\n",
    "可以直接使用PaddleTS集成的公开数据集，也可以导入自己的数据（如何导入自己的数据请参考TSDataset相关使用文档）  \n",
    "\n",
    "在这个例子里面，示例数据集是一份包含了2010年至2014年的关于天气的单变量数据，其中 WetBulbCelsuis 代表湿球温度。可通过下面代码导入： "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c8230a9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from paddlets.datasets.repository import get_dataset\n",
    "\n",
    "tsdataset = get_dataset(\"UNI_WTH\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8329500d",
   "metadata": {},
   "source": [
    "## 1.2 数据查看\n",
    "\n",
    "PaddleTS提供了统一的TSDataset数据集接口描述时序数据。对于导入完成的数据集，可以调用TSDataset提供的接口查看数据的基本情况。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c48d185",
   "metadata": {},
   "source": [
    "从下方代码运行结果看出，该数据的起始时间为2010-01-01 00:00:00，结束时间为2013-12-31 23:00:00，时间点频率为小时级（H）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c3ce3069",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "start time: 2010-01-01 00:00:00\n",
      "end time: 2013-12-31 23:00:00\n",
      "frequency: H\n"
     ]
    }
   ],
   "source": [
    "print(f\"start time: {tsdataset.target.start_time}\")\n",
    "print(f\"end time: {tsdataset.target.end_time}\")\n",
    "print(f\"frequency: {tsdataset.target.freq}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ce16963",
   "metadata": {},
   "source": [
    "也可通过TSDataset.plot接口可视化查看数据集。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "bcd0c8e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date'>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tsdataset.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b76ef7c3",
   "metadata": {},
   "source": [
    "## 1.3 数据预处理\n",
    "\n",
    "在建模之前，确定训练集和测试集。在该示例中使用前65%数据用于训练，后35%数据用于测试。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e6b9e3de",
   "metadata": {},
   "outputs": [],
   "source": [
    "from paddlets.transform import StandardScaler\n",
    "\n",
    "# 数据集拆分\n",
    "train_tsdataset, test_tsdataset = tsdataset.split(split_point=0.65)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83cbf938",
   "metadata": {},
   "source": [
    "确认训练集和数据集之后，我们对数据进行标准化处理。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "12cdba1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 数据标准化\n",
    "scaler = StandardScaler()\n",
    "scaler.fit(train_tsdataset)\n",
    "train_tsdataset_scaled = scaler.transform(train_tsdataset)\n",
    "test_tsdataset_scaled = scaler.transform(test_tsdataset)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b041b140",
   "metadata": {},
   "source": [
    "## 1.4 模型构建\n",
    "\n",
    "完成数据预处理之后，我们需要构建时序预测模型。在该示例中，我们会基于[sklearn.neighbors.KNeighborsRegressor](https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsRegressor.html)构建时序预测模型。\n",
    "\n",
    "构建方式非常简单，调用PaddleTS提供的模型构建接口，传入希望使用的第三方模型以及时序相关参数即可。这里我们假定希望模型使用过去的3个时间点去预测未来的1个时间点："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a8a2bbed",
   "metadata": {},
   "outputs": [],
   "source": [
    "from paddlets.models.ml_model_wrapper import make_ml_model\n",
    "\n",
    "from sklearn.neighbors import KNeighborsRegressor\n",
    "\n",
    "forecasting_model = make_ml_model(\n",
    "    model_class=KNeighborsRegressor,\n",
    "    in_chunk_len=3,\n",
    "    out_chunk_len=1\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4bbb1209",
   "metadata": {},
   "source": [
    "## 1.5 模型训练\n",
    "\n",
    "完成模型构建和数据处理后，即可进行模型训练。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "478e2c34",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "np.random.seed(2022)\n",
    "forecasting_model.fit(train_data=train_tsdataset_scaled)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48a3bc4e",
   "metadata": {},
   "source": [
    "## 1.6 模型预测与评估\n",
    "\n",
    "模型训练完成之后，可以对测试集进行预测并评估。   \n",
    "\n",
    "PaddleTS的 [metrics][metrics Link] 模块提供了多种评估指标，该示例中采用MAE。\n",
    "\n",
    "[metrics Link]: https://github.com/PaddlePaddle/PaddleTS/blob/main/paddlets/metrics/metrics.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d266d630",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mae: {'WetBulbCelsius': 0.032317469862445325}\n"
     ]
    }
   ],
   "source": [
    "from paddlets.metrics import MAE\n",
    "\n",
    "# 预测\n",
    "y_pred = forecasting_model.predict(train_tsdataset_scaled)\n",
    "\n",
    "# 基于真实数据和预测结果，计算MAE评估指标\n",
    "y_true, _ = test_tsdataset_scaled.split(test_tsdataset_scaled.target.time_index[0])\n",
    "\n",
    "mae = MAE()\n",
    "metric_res = mae(tsdataset_true=y_true, tsdataset_pred=y_pred)\n",
    "print(f\"mae: {metric_res}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "758425bf",
   "metadata": {},
   "source": [
    "## 1.7 模型保存\n",
    "\n",
    "模型训练完成之后，可以将其保存到指定路径。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c0773e02",
   "metadata": {},
   "outputs": [],
   "source": [
    "forecasting_model.save(\"./forecasting_model\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfdeda2e",
   "metadata": {},
   "source": [
    "## 1.8 模型加载及推理\n",
    "\n",
    "可以加载已保存的模型用于新数据的预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d74ba1a0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            WetBulbCelsius\n",
      "2014-01-01       -0.400627\n"
     ]
    }
   ],
   "source": [
    "from paddlets.models.model_loader import load\n",
    "\n",
    "loaded_forecasting_model = load(\"./forecasting_model\")\n",
    "pred_tsdataset = loaded_forecasting_model.predict(test_tsdataset_scaled)\n",
    "print(pred_tsdataset)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb537f9f",
   "metadata": {},
   "source": [
    "## 1.9 自定义样本数据构建函数\n",
    "\n",
    "一些第三方库（如 scikit-learn ）的机器学习模型通常会接收numpy.ndarray类型数据作为 fit 和 predict 方法的输入。但是在PaddleTS中，会使用 paddlets.models.forecasting.ml.adapter.ml_dataloader.MLDataLoader 表示可用于训练/预测的时序数据。\n",
    "\n",
    "因此，make_ml_model 提供了 udf_ml_dataloader_to_fit_ndarray 和 udf_ml_dataloader_to_predict_ndarray 两个可选参数，用于支持用户将 MLDataLoader 转换为 numpy.ndarray 数据对象。\n",
    "\n",
    "make_ml_model 默认会使用 default_sklearn_ml_dataloader_to_fit_ndarray 和 default_sklearn_ml_dataloader_to_predict_ndarray 两个函数将 MLDataLoader 分别转换为 fit 和 predict 方法可接收的 numpy.ndarray 数据。同时，用户也可以开发自定义的数据转换函数，用于得到可用于训练/预测的数据。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecc9113b",
   "metadata": {},
   "source": [
    "### 1.9.1 自定义udf函数\n",
    "\n",
    "下方示例展示了如何定义2个udf函数，需要注意的是，由于这个小节的主要目的是为了说明如何使用自定义udf函数这个功能。因此，下方示例的函数逻辑与PaddleTS提供的默认函数逻辑几乎相同。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1271a6e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from typing import Tuple, Any, Optional, Dict\n",
    "import numpy as np\n",
    "import itertools\n",
    "\n",
    "\n",
    "def udf_sklearn_ml_dataloader_to_fit_ndarray(\n",
    "    ml_dataloader: \"MLDataLoader\",\n",
    "    model_init_params: Dict[str, Any],\n",
    "    in_chunk_len: int,\n",
    "    skip_chunk_len: int,\n",
    "    out_chunk_len: int\n",
    ") -> Tuple[np.ndarray, Optional[np.ndarray]]:\n",
    "    \"\"\"\n",
    "    udf函数，自定义fit接口的数据构建逻辑。\n",
    "    \"\"\"\n",
    "    data = next(ml_dataloader)\n",
    "\n",
    "    sample_x_keys = data.keys() - {\"future_target\"}\n",
    "    if in_chunk_len < 1:\n",
    "        sample_x_keys -= {\"past_target\"}\n",
    "    full_ordered_x_key_list = [\"past_target\"]\n",
    "    full_ordered_x_key_list.extend(\n",
    "        [f\"{t[1]}_{t[0]}\" for t in itertools.product([\"numeric\", \"categorical\"], [\"known_cov\", \"observed_cov\", \"static_cov\"])]\n",
    "    )\n",
    "    \n",
    "    actual_ordered_x_key_list = []\n",
    "    for k in full_ordered_x_key_list:\n",
    "        if k in sample_x_keys:\n",
    "            actual_ordered_x_key_list.append(k)\n",
    "\n",
    "    reshaped_x_ndarray_list = []\n",
    "    for k in actual_ordered_x_key_list:\n",
    "        ndarray = data[k]\n",
    "        reshaped_ndarray = ndarray.reshape(ndarray.shape[0], ndarray.shape[1] * ndarray.shape[2])\n",
    "        reshaped_x_ndarray_list.append(reshaped_ndarray)\n",
    "    \n",
    "    x = np.hstack(tup=reshaped_x_ndarray_list)\n",
    "    y = np.squeeze(data[\"future_target\"])\n",
    "    return x, y\n",
    "\n",
    "\n",
    "def udf_sklearn_ml_dataloader_to_predict_ndarray(\n",
    "    ml_dataloader: \"MLDataLoader\",\n",
    "    model_init_params: Dict[str, Any],\n",
    "    in_chunk_len: int,\n",
    "    skip_chunk_len: int,\n",
    "    out_chunk_len: int\n",
    ") -> Tuple[np.ndarray, Optional[np.ndarray]]:\n",
    "    \"\"\"\n",
    "    udf函数，自定义predict接口的数据构建逻辑。\n",
    "    \"\"\"\n",
    "    data = next(ml_dataloader)\n",
    "\n",
    "    sample_x_keys = data.keys() - {\"future_target\"}\n",
    "    if in_chunk_len < 1:\n",
    "        sample_x_keys -= {\"past_target\"}\n",
    "    full_ordered_x_key_list = [\"past_target\"]\n",
    "    full_ordered_x_key_list.extend(\n",
    "        [f\"{t[1]}_{t[0]}\" for t in itertools.product([\"numeric\", \"categorical\"], [\"known_cov\", \"observed_cov\", \"static_cov\"])]\n",
    "    )\n",
    "    \n",
    "    actual_ordered_x_key_list = []\n",
    "    for k in full_ordered_x_key_list:\n",
    "        if k in sample_x_keys:\n",
    "            actual_ordered_x_key_list.append(k)\n",
    "\n",
    "    reshaped_x_ndarray_list = []\n",
    "    for k in actual_ordered_x_key_list:\n",
    "        ndarray = data[k]\n",
    "        reshaped_ndarray = ndarray.reshape(ndarray.shape[0], ndarray.shape[1] * ndarray.shape[2])\n",
    "        reshaped_x_ndarray_list.append(reshaped_ndarray)\n",
    "    \n",
    "    x = np.hstack(tup=reshaped_x_ndarray_list)\n",
    "    return x, None"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ce070b4",
   "metadata": {},
   "source": [
    "### 1.9.2 使用udf函数作为可选参数构建时序预测模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "55e6979b",
   "metadata": {},
   "outputs": [],
   "source": [
    "forecasting_model_with_udf_fn = make_ml_model(\n",
    "    model_class=KNeighborsRegressor,\n",
    "    in_chunk_len=3,\n",
    "    out_chunk_len=1,\n",
    "    udf_ml_dataloader_to_fit_ndarray=udf_sklearn_ml_dataloader_to_fit_ndarray,\n",
    "    udf_ml_dataloader_to_predict_ndarray=udf_sklearn_ml_dataloader_to_predict_ndarray\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f2acc65",
   "metadata": {},
   "source": [
    "### 1.9.3 训练与预测\n",
    "\n",
    "模型构建完成后，训练与预测的步骤与上文 1.4 - 1.6 完全相同。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "961ece4c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     WetBulbCelsius\n",
      "2012-08-07 15:00:00        1.702946\n"
     ]
    }
   ],
   "source": [
    "# 训练\n",
    "forecasting_model_with_udf_fn.fit(train_data=train_tsdataset_scaled)\n",
    "\n",
    "# 预测\n",
    "y_pred = forecasting_model_with_udf_fn.predict(train_tsdataset_scaled)\n",
    "print(y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "114277aa",
   "metadata": {},
   "source": [
    "# 2. 基于第三方模型进行时序异常检测\n",
    "\n",
    "这部分会基于 [pyod][pyod Link] 第三方模型构建时序异常检测模型。步骤包括：\n",
    "\n",
    "- 2.1 数据导入\n",
    "- 2.2 数据查看\n",
    "- 2.3 数据预处理\n",
    "- 2.4 模型构建\n",
    "- 2.5 模型训练\n",
    "- 2.6 模型预测与评估\n",
    "- 2.7 模型结果可视化\n",
    "- 2.8 模型保存  \n",
    "- 2.9 模型加载及推理\n",
    "- 2.10 （可选）自定义样本数据构建函数\n",
    "\n",
    "[pyod Link]: https://pyod.readthedocs.io/en/latest/"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fecf750",
   "metadata": {},
   "source": [
    "## 2.1 数据导入\n",
    "\n",
    "使用PaddleTS内置的公开数据集NAB。可通过下方代码导入：  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "061d4ccf",
   "metadata": {},
   "outputs": [],
   "source": [
    "from paddlets.datasets.repository import get_dataset\n",
    "\n",
    "tsdataset = get_dataset('NAB_TEMP')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f9ef502",
   "metadata": {},
   "source": [
    "## 1.2 数据查看\n",
    "\n",
    "PaddleTS提供了异常检测数据的可视化接口，用户查看数据情况，见下方示例代码："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "929f45e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from paddlets.utils.utils import plot_anoms\n",
    "\n",
    "plot_anoms(origin_data=tsdataset, feature_name=\"value\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94fb7732",
   "metadata": {},
   "source": [
    "## 2.3 数据预处理\n",
    "\n",
    "在建模之前，确定训练集和测试集。在该示例中使用前15%数据用于训练，后85%数据用于测试。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "88433ccd",
   "metadata": {},
   "outputs": [],
   "source": [
    "from paddlets.transform import StandardScaler\n",
    "\n",
    "# 数据集拆分\n",
    "train_tsdataset, test_tsdataset = tsdataset.split(0.15)\n",
    "\n",
    "# 标准化\n",
    "scaler = StandardScaler()\n",
    "scaler.fit(train_tsdataset)\n",
    "train_tsdataset_scaled = scaler.transform(train_tsdataset)\n",
    "test_tsdataset_scaled = scaler.transform(test_tsdataset)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31439a9d",
   "metadata": {},
   "source": [
    "## 2.4 模型构建\n",
    "\n",
    "完成数据预处理之后，我们需要构建时序预测模型。在该示例中，我们会基于 [pyod.models.pca.PCA][pca Link] 构建时序异常检测模型。这里假定样本窗口大小为2。\n",
    "\n",
    "[pca Link]: https://pyod.readthedocs.io/en/latest/pyod.models.html#pyod.models.pca.PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b29fcf0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from paddlets.models.ml_model_wrapper import make_ml_model\n",
    "\n",
    "from pyod.models.pca import PCA\n",
    "\n",
    "anomaly_model = make_ml_model(model_class=PCA, in_chunk_len=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ca80eb8",
   "metadata": {},
   "source": [
    "## 2.5 模型训练\n",
    "\n",
    "完成模型构建和数据处理后，即可进行模型训练。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e81a7dfb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "np.random.seed(2022)\n",
    "anomaly_model.fit(train_data=train_tsdataset_scaled)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "242cf08f",
   "metadata": {},
   "source": [
    "## 2.6 模型预测与评估\n",
    "\n",
    "模型训练完成之后，可以对测试集进行预测并评估。   \n",
    "\n",
    "PaddleTS的 [metrics][metrics Link] 模块提供了多种评估指标，该示例中采用F1，Precision，Recall三个指标进行评估。\n",
    "\n",
    "[metrics Link]: https://github.com/PaddlePaddle/PaddleTS/blob/main/paddlets/metrics/metrics.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c2a58b9e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[2022-11-02 19:19:17,164] [paddlets.metrics.base] [WARNING] Tsdataset true's and pred's time_index do not match, the result will be calculated according to the intersection!\n",
      "[2022-11-02 19:19:17,184] [paddlets.metrics.base] [WARNING] Tsdataset true's and pred's time_index do not match, the result will be calculated according to the intersection!\n",
      "[2022-11-02 19:19:17,201] [paddlets.metrics.base] [WARNING] Tsdataset true's and pred's time_index do not match, the result will be calculated according to the intersection!\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "f1 metric: 0.5914179104477612\n",
      "precision metric: 0.6277227722772277\n",
      "recall metric: 0.5590828924162258\n"
     ]
    }
   ],
   "source": [
    "from paddlets.metrics import F1, Precision, Recall\n",
    "\n",
    "# 预测\n",
    "pred_label = anomaly_model.predict(test_tsdataset_scaled)\n",
    "lable_name = pred_label.target.data.columns[0]\n",
    "\n",
    "# 计算评估指标\n",
    "f1 = F1()\n",
    "f1_metric_res = f1(tsdataset_true=test_tsdataset, tsdataset_pred=pred_label)\n",
    "\n",
    "precision = Precision()\n",
    "precision_metric_res = precision(tsdataset_true=test_tsdataset, tsdataset_pred=pred_label)\n",
    "\n",
    "recall = Recall()\n",
    "recall_metric_res = recall(tsdataset_true=test_tsdataset, tsdataset_pred=pred_label)\n",
    "\n",
    "print (f\"f1 metric: {f1_metric_res[lable_name]}\")\n",
    "print (f\"precision metric: {precision_metric_res[lable_name]}\")\n",
    "print (f\"recall metric: {recall_metric_res[lable_name]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5beea26f",
   "metadata": {},
   "source": [
    "## 2.7 模型结果可视化 \n",
    "\n",
    "可以将模型的预测结果和真实异常做对比，更加直观的查看模型预测的效果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a50793ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_anoms(origin_data=test_tsdataset, predict_data=pred_label, feature_name=\"value\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8dd1d61b",
   "metadata": {},
   "source": [
    "在异常检测场景中，PaddleTS除了提供predict接口预测每个时间点是否异常，还提供了predict_score接口获得每个时间点的异常分数，分数越高，表示该点越可能是异常。见下方示例代码："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "eda07d41",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 异常评分与真实值\n",
    "pred_score = anomaly_model.predict_score(test_tsdataset_scaled)\n",
    "plot_anoms(origin_data=test_tsdataset, predict_data=pred_score, feature_name=\"value\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b5203f1",
   "metadata": {},
   "source": [
    "## 2.8 模型保存\n",
    "\n",
    "模型训练完成之后，可以将其保存到指定路径。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "373e5b9e",
   "metadata": {},
   "outputs": [],
   "source": [
    "anomaly_model.save('./anomaly_pca_model')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17c21147",
   "metadata": {},
   "source": [
    "## 2.9 模型加载及推理\n",
    "\n",
    "可以加载已保存的模型用于新数据的预测："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "49279e77",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pred_label: \n",
      "                     label\n",
      "timestamp                 \n",
      "2013-12-14 16:55:00      0\n",
      "2013-12-14 17:00:00      0\n",
      "2013-12-14 17:05:00      0\n",
      "2013-12-14 17:10:00      0\n",
      "2013-12-14 17:15:00      0\n",
      "...                    ...\n",
      "2014-02-19 15:05:00      0\n",
      "2014-02-19 15:10:00      0\n",
      "2014-02-19 15:15:00      0\n",
      "2014-02-19 15:20:00      0\n",
      "2014-02-19 15:25:00      0\n",
      "\n",
      "[19279 rows x 1 columns]\n",
      "pred_score: \n",
      "                     label_score\n",
      "timestamp                       \n",
      "2013-12-14 16:55:00  1221.563650\n",
      "2013-12-14 17:00:00  1257.307292\n",
      "2013-12-14 17:05:00  1272.464580\n",
      "2013-12-14 17:10:00  1188.761339\n",
      "2013-12-14 17:15:00  1256.563297\n",
      "...                          ...\n",
      "2014-02-19 15:05:00  1213.258473\n",
      "2014-02-19 15:10:00  1248.840452\n",
      "2014-02-19 15:15:00  1223.282235\n",
      "2014-02-19 15:20:00  1200.807306\n",
      "2014-02-19 15:25:00  1233.421097\n",
      "\n",
      "[19279 rows x 1 columns]\n"
     ]
    }
   ],
   "source": [
    "from paddlets.models.model_loader import load\n",
    "\n",
    "loaded_anomaly_model = load(\"./anomaly_pca_model\")\n",
    "pred_label = loaded_anomaly_model.predict(test_tsdataset_scaled)\n",
    "print(f\"pred_label: \\n{pred_label}\")\n",
    "\n",
    "pred_score = loaded_anomaly_model.predict_score(test_tsdataset_scaled)\n",
    "print(f\"pred_score: \\n{pred_score}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8741146",
   "metadata": {},
   "source": [
    "验证加载的模型的预测结果，与保存前的结果一致："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a0d9fcac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_anoms(origin_data=test_tsdataset, predict_data=pred_label, feature_name=\"value\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d96ddf15",
   "metadata": {},
   "source": [
    "## 2.10 自定义样本数据构建函数\n",
    "\n",
    "这部分内容与时序预测模型的处理方式相同，可参考上文 1.9 小节。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
